Our long-term goal is to understand the detailed molecular mechanisms that connect genotype, phenotype and response to therapy in lysosomal storage diseases (LSDs). LSDs are a family of genetic metabolic diseases caused by lysosomal enzyme deficiencies. In this project we use Fabry disease as a model system to develop a bioinformatics-based paradigm to address two fundamental issues: 1) The relationship between genotype and phenotype in LSDs. This task is challenging because in LSDs different mutations in the same enzyme often lead to different disease phenotypes. 2) The relationship between genotype and response to "pharmacological chaperone" therapy. Pharmacological chaperones are small-molecule ligands that are used to rescue mutants, resulting in increased enzymatic activity; several Fabry mutations have been shown to be rescueable in this way. The same therapy is likely to be useful for other LSDs, particularly those with neurological involvement, for which enzyme replacement therapy is not viable. The two aims of this application address, at different levels, both issues described above. The first aim, tests the hypothesis that knowing the change that occurs in the protein sequence, together with the structural environment in which it occurs, is sufficient to predict the resulting disease phenotype and response to pharmacological chaperone therapy. This is tested through the rigorous training of classification methods using sequence and structure-derived descriptors for a large set of Fabry mutants of known phenotype. The resulting classification provides a large- scale quantitative description of the correlation between genotype and phenotype. The accuracy of predictions based on this approach is a measure of how much information about the genotype the descriptors contain. The same approach will be used to establish a quantitative correlation between genotype and response to pharmacological chaperone therapy. Finally, applying the classification methods to mutations in other LSDs will test the generality of the approach. The second aim of this application addresses the issue of genotype/phenotype correlation from a biophysical point of view. We test the hypothesis that a combination of factors, mainly folding free energy, ligand binding affinity, and relative pH stability of the mutants determines the disease phenotype and response to pharmacological chaperone therapy. This is done analyzing selected mutants using molecular modeling and molecular dynamics simulations of the enzyme/ligand and enzyme/receptor interactions, as well as, pH stability, and other calculations. The methods used in the second aim are very detailed, but are not applicable at a large scale. Thus, both aims provide complementary views of genotype/phenotype correlation in LSDs. The successful completion of this project will, for the first time, provide a quantitative connection between genotype and phenotype in LSDs and a detailed biophysical description of the molecular mechanisms underlying genotype/phenotype correlations and response to pharmacological chaperone therapy in Fabry disease. Relevance of this research to public health. Lysosomal storage diseases (LSDs) are a group of more than 40 genetic metabolic disorders. Worldwide, the incidence of patients with LSDs is estimated to be ~ 1 in 8,000 live births. Understanding the correlation between genotype, phenotype, and response to treatment in these diseases will help in their diagnosis and treatment, particularly for LSDs that affect the brain, for which no effective treatment is available to date. [unreadable] [unreadable] [unreadable]